Portfolio managers and traders can use a testing methodology for several reasons, such as: (i) a guide to evaluate past performance and actual returns in relation to the risks incurred to achieve them; (ii) an analytical tool to understand risk exposures and to optimize portfolios; and (iii) a forward-looking measurement tool to predict future volatility. Despite the increased use of complex portfolio analytical tools, risk models, and testing methodologies, the accurate measurement of risk and construction of portfolios presents many practical challenges.
Traditionally, portfolio managers and traders buy securities with a positive attribute and avoid or sell short those with a negative attribute. This methodology, although valid for long/short portfolios, is not appropriate for long-only portfolios. In a long/short portfolio, managers can add value by identifying not only those stocks likely to outperform their benchmark, but also those stocks likely to underperform. By buying the strong performers and selling the underperformers short, a manager can achieve a positive return while minimizing risk. In the context of a long-only portfolio, the constraint imposed by not being able to short a position makes the conclusions from traditional testing methodologies inapplicable and inappropriate.
For example, a long-only portfolio manager might strongly believe that a company, which constitutes 2% of her benchmark, will go bankrupt. The only way the manager can express this belief is to not hold the stock at all. In a long/short portfolio, though, the manager can bet against the company as strongly as the manager can normally bet for a company. The ability to short-sell gives a manager more flexibility. A need therefore exists for a signal testing methodology that can predict performance, allocate securities, and minimize risk, while accounting for limitations imposed by a long-only portfolio.